CN112205007B

CN112205007B - System and method for better resource utilization in 5G networks using an enabling layer

Info

Publication number: CN112205007B
Application number: CN201980036724.2A
Authority: CN
Inventors: 拉马纳坦·帕拉尼亚潘; 拉特纳卡·拉奥·文卡塔·拉瓦拉普; 普拉卡什·拉奥
Original assignee: Samsung Electronics Co Ltd
Current assignee: Samsung Electronics Co Ltd
Priority date: 2018-06-01
Filing date: 2019-05-31
Publication date: 2022-11-01
Anticipated expiration: 2039-05-31
Also published as: EP3750335A4; CN112205007A; US10863344B2; WO2019231275A1; US20190373443A1; EP3750335A1

Abstract

A method for improving resource utilization in a 5G network, comprising: at least one network parameter is determined in response to a request received from a user for at least one service at a particular location, wherein the at least one network parameter includes at least one of availability of at least one edge server, round Trip Time (RTT), end-to-end (E2E) delay, and network tier. Further, the method includes providing at least one recommendation for performing the at least one requested service on the UE based on the determined at least one network parameter. The at least one recommendation includes at least one of an application, a RAT, a SIM, and a network slice of the SIM.

Description

System and method for better resource utilization in 5G networks using an enabling layer

Technical Field

The present disclosure relates to the field of Mobile Edge Computing (MEC), and more particularly, to determining availability of network resources in a 5 th generation (5G) network to provide recommendations to improve resource utilization of User Equipment (UE).

Background

In fifth generation (5G) networks, there are several requirements and architectural enablers for enabling low latency communication and application component offloading. Low latency communication and application component offloading may improve delivery of content and applications to/from a user. To support such low latency communication and application component offloading, mobile Edge Computing (MEC) has been developed. In MEC, a Mobile Edge Computing Server (MECs)/edge server may be placed near an access point (AP base station communicating with User Equipment (UE)) in a mobile network. Thus, MEC enables operators to better adapt traffic to current radio conditions, optimize quality of service and improve network efficiency. Applications for MECs include autopilot, gaming, virtual/Augmented Reality (AR), telesurgery, etc.

In a conventional approach, the UE requests a list of available user applications for a particular service from the edge server and notifies the user of the user applications available at the edge server for the particular service. However, at any point in time, the performance of a user application may vary due to a number of factors including, but not limited to, current location, network load, network resources (e.g., edge servers, radio Access Technologies (RATs)), availability of network slices, and so forth.

Disclosure of Invention

Technical problem

A primary object of embodiments herein is to disclose methods and systems for providing a recommendation based on an availability of network resources to complete at least one service by a User Equipment (UE) in a particular location, wherein the recommendation includes at least one of an application, a Subscriber Identity Module (SIM), a network slice, a Radio Access Technology (RAT), and the like.

It is another object of embodiments herein to disclose a method and system for determining availability of an edge server for one or more applications supporting at least one service.

It is another object of embodiments herein to disclose methods and systems for recommending an application for completing a requested service based on at least one of a round trip time and an end-to-end (E2E) delay determined for one or more applications supporting the requested service.

It is another object of embodiments herein to disclose methods and systems that enable a UE to provide information about network parameters to an edge server and query the edge server to recommend an application to complete a requested service.

It is another object of embodiments herein to disclose methods and systems for determining a network class to recommend at least one of an application, RAT/subscription, and SIM to complete a requested service at a specific location.

Solution to the problem

It is another object of embodiments herein to disclose methods and systems for determining availability of an edge server for one or more applications supporting at least one service.

It is another object of embodiments herein to disclose methods and systems for recommending for completion of a requested service based on at least one of a round trip time and an end-to-end (E2E) delay determined for one or more applications supporting the requested service.

Drawings

Embodiments herein are illustrated in the accompanying drawings, in which like reference numerals refer to corresponding parts throughout the drawings. The embodiments herein will be better understood by the following description with reference to the accompanying drawings, in which:

FIGS. 1a and 1b illustrate a communication system for providing recommendations to a user to complete a service at a particular location according to embodiments disclosed herein;

FIG. 2 is an example block diagram illustrating various elements of an enabling module for providing recommendations to complete a service for a User Equipment (UE) in accordance with embodiments disclosed herein;

FIG. 3 is a flow chart illustrating a method for providing recommendations to complete a service of a UE at a particular location according to embodiments disclosed herein;

fig. 4a is a flowchart illustrating a method for recommending an application for completing a particular service of a UE at a particular location based on at least one of RTT and E2E delay, according to embodiments disclosed herein;

FIG. 4b is a flow diagram illustrating a method for providing recommendations for services by querying a cloud server in accordance with embodiments disclosed herein;

FIG. 4c is a flow diagram illustrating a method for providing recommendations for a requested service based on network ratings according to embodiments disclosed herein;

5a, 5b and 5c are example diagrams illustrating a recommendation of an application for a requested service based on RTT according to embodiments disclosed herein;

fig. 6a and 6b are example diagrams illustrating recommendation of an application for a call related service based on E2E delay according to embodiments disclosed herein;

fig. 7 is an example diagram illustrating recommending, by a cloud server, an application for a particular service in accordance with an embodiment disclosed herein;

fig. 8 is an example sequence diagram illustrating determining availability of an edge server for one or more applications according to embodiments disclosed herein.

9a, 9b, and 9c are exemplary diagrams illustrating the creation of a folder structure for indicating the availability of an edge server for one or more applications according to embodiments disclosed herein;

FIG. 9d is an example diagram illustrating the allocation of badge notifications for one or more applications available at an edge server in accordance with embodiments disclosed herein;

FIG. 9e is an example diagram illustrating providing a user notification indicating availability of an edge server in accordance with embodiments disclosed herein;

FIG. 10 depicts an exemplary diagram in which a local memory is adapted with an edge server to offload downloaded content without user intervention content in accordance with embodiments disclosed herein;

11 a-11 h depict example tables in which values of the table may be used to determine network rank according to embodiments disclosed herein;

fig. 12 is an example flow diagram illustrating a recommendation of a RAT to complete a requested service at a particular location based on a network tier according to embodiments disclosed herein;

figure 13 is an example table illustrating the availability of network slices for edge servers/SIMs recommending applications for a requested service at a particular location according to embodiments disclosed herein;

14a and 14b depict example tables in which the values of the example tables are used to recommend SIMs for a requested service at a particular location in accordance with embodiments disclosed herein;

15a and 15b are example diagrams illustrating a recommendation of a SIM for a requested service at a particular location according to embodiments disclosed herein;

16a, 16b, 16c, and 16d are exemplary diagrams illustrating recommending a network slice from one or more network slices associated with one or more SIMs for a requested service according to embodiments disclosed herein;

17a and 17b are exemplary diagrams illustrating updating network capabilities based on a cell change to recommend at least one of a network slice and a RAT for a requested service according to embodiments disclosed herein;

fig. 18 is an exemplary diagram illustrating feature-based quality of service (QoS) operations for call-related applications according to embodiments disclosed herein;

FIG. 19 is an example flow diagram illustrating processing of at least one of network slices and edge availability to recommend an application for a particular service in accordance with an embodiment disclosed herein; and

FIG. 20 is an example diagram illustrating providing recommendations to complete a service (or services) at a particular location according to embodiments disclosed herein.

Detailed Description

Before proceeding with the following detailed description, it may be advantageous to set forth definitions of certain words and phrases used throughout this patent document: the terms "comprise" and "include," as well as derivatives thereof, mean inclusion without limitation; the term "or" is inclusive, meaning and/or; the phrases "and 8230; \ 8230, associated with" and "associated with" and their derivatives may mean including, included with, associated with, including with, 8230; \8230, associated with, including, included with, for example \8230, within, connected with, or associated with \8230; \8230, connected with, coupled with, or associated with, 8230, coupled with, capable of being associated with, for example, 8230, communication with, for example, 8230, collaboration, interleaving, juxtaposition, proximity to, for example, 8230, binding to, having, for example, 8230, attributes, etc. The term "controller" refers to any device, system or part thereof that controls at least one operation, such a device may be implemented in hardware, firmware or software, or some combination of at least two of the same. It should be noted that the functionality associated with any particular controller may be centralized or distributed, whether locally or remotely.

Further, the various functions described below may be implemented or supported by one or more computer programs, each formed from computer readable program code and embodied in a computer readable medium. The terms "application" and "program" refer to one or more computer programs, software components, sets of instructions, procedures, functions, objects, classes, instances, related data, or a portion thereof adapted for implementation in suitable computer readable program code. The phrase "computer readable program code" includes any type of computer code, including source code, object code, and executable code. The phrase "computer readable medium" includes any type of medium capable of being accessed by a computer, such as Read Only Memory (ROM), random Access Memory (RAM), a hard disk drive, a Compact Disc (CD), a Digital Video Disc (DVD), or any other type of memory. A "non-transitory" computer-readable medium does not include a wired, wireless, optical, or other communication link that transmits transitory electrical or other signals. Non-transitory computer-readable media include media that can permanently store data as well as media that can store data and subsequently overwrite, such as a rewritable optical disc or an erasable memory device.

Definitions for certain words and phrases are provided throughout this patent document. Those of ordinary skill in the art should understand that in many, if not most instances, such definitions apply to prior, as well as future uses of such defined words and phrases.

Figures 1 through 20, discussed below, and the various embodiments used to describe the principles of the present disclosure in this patent document are by way of illustration only and should not be construed in any way to limit the scope of the disclosure. Those skilled in the art will understand that the principles of the present disclosure may be implemented in any suitably arranged system or device.

The exemplary embodiments herein and the various features and advantageous details thereof are explained with reference to the non-limiting embodiments shown in the drawings and in the following description. Descriptions of well-known components and processing techniques are omitted so as to not unnecessarily obscure the embodiments herein. The description herein is intended merely to facilitate an understanding of ways in which the example embodiments herein may be practiced and to further enable those of skill in the art to practice the example embodiments herein. Accordingly, the disclosure should not be construed as limiting the scope of the example embodiments herein.

Embodiments herein disclose methods and systems for providing recommendations to complete at least one service by a User Equipment (UE) in a particular location, wherein the recommendations include at least one of an application, a Radio Access Technology (RAT)/subscription, a Subscriber Identity Module (SIM), a network slice of one or more SIMs, and the like. Referring now to the drawings, and more particularly to fig. 1-20, wherein like reference numerals designate corresponding features throughout the several views, there is shown an exemplary embodiment.

Fig. 1a and 1b illustrate a communication system 100 for providing recommendations to a user to complete a service at a particular location according to embodiments disclosed herein. Communication system 100 may be configured to provide content such as, but not limited to, voice, data, video, message broadcasts, etc., to a plurality of users in accordance with the European Telecommunications Standards Institute (ETSI) Mobile Edge Computing (MEC). Communication system 100 includes user equipment 102, base stations 104 a-104 n, and edge servers 106a-106 n.

The UE 102 referred to herein may be any device that supports one or more Subscriber Identity Modules (SIMs) and includes 5G device features. Examples of the UE 102 may be, but are not limited to, a cell phone, a smart phone, a tablet, a Personal Digital Assistant (PDA), a laptop, a computer, a wearable computing device, a vehicle infotainment device, an internet of things (IoT) device, a medical device, and any other processing device connected to a wireless modem or having Radio Frequency (RF) processing capabilities. Further, one or more SIMs supported by the UE 102 may be operated by different service providers/operators. The UE 102 may include one or more physical SIMs, and/or one or more virtual SIMs.

UE 102 may connect to at least one base station (104 a to 104 n) over the air. The base stations (104 a, 104 n) may serve cells of different Radio Access Technologies (RATs). Examples of a RAT may be, but are not limited to, generation 5 (5G), long Term Evolution (LTE), LTE advanced, 3 rd generation partnership project (3 GPP), wideband Code Division Multiple Access (WCDMA) system, high speed access data (HSPA), global system for mobile communications/enhanced data rates for GSM evolution (GSM/EDEGE), worldwide interoperability for microwave access (WiMax), ultra Mobile Broadband (UMB), wi-Fi, and the like. One or more SIMs of the UE 104 may support different RATs/subscriptions.

According to the ETSI-based MEC, at least one edge server (106 a to 106 n) may be placed near any of the base stations 104a to 104n in communication with the UE 102 to enable low latency communication and application content offloading. The edge servers 106a-106n may provide computing resources, storage capacity, connectivity, and access to information about the RATs. The edge servers 106a-106n may support various applications (e.g., without limitation, video streaming related applications, security chassis applications, ioT related applications, augmented Reality (AR) related applications, etc.) and content (e.g., files, video, audio, etc.) that may be offloaded to nearby UEs 102. Thus, the delivery of content and applications to users is improved.

As shown in fig. 1b, the communication system 100 may also include a cloud server 116 (server instance of a service) that supports multiple services. Further, the edge servers 106a-106n may support some services supported by the cloud server 116.

In addition, UE 102 includes memory 108, an enabling module/enabling layer module 110, a communication interface module 112, and a display module 114. The UE 102 may also connect to at least one external server and application server by utilizing at least one of the internet, wired networks (local area network (LAN), ethernet, etc.), wireless networks (Wi-Fi network, cellular network, wi-Fi hotspot, bluetooth, zigbee, etc.), etc., to download applications for services that the UE 102 may support. Examples of applications referenced herein may be, but are not limited to, call-related applications, over-the-top (OTT) applications, streaming media applications, file download-related applications, ioT-related applications, augmented Reality (AR) -related applications, and the like. Examples of services mentioned herein may be, but are not limited to, streaming media services (streaming multimedia data, e.g. audio, video, text, etc.), call related services, file download services, carousel services (combining file download services and streaming media services), television (TV) services, on-demand media services, etc. Additionally, the UE 102 may connect to a local database/memory 108 and an external database to provide content (e.g., files, data, video, audio, etc.) to the user.

The enablement module 110 may include at least one of a single processor, multiple processors, multiple homogeneous cores, multiple heterogeneous cores, multiple Central Processing Units (CPUs) of different kinds, and the like. The enablement module 110 operates by supporting the functionality of the enablement layer. The enablement layer works in conjunction with at least one of the edge server and the application server to provide content (video, audio, files, etc.) and applications to the user.

In embodiments, the enablement module 110 may be configured to provide recommendations to complete a service requested by a user at a particular location. The recommendation may be at least one of availability of an edge server, an application, a SIM, a network slice of a SIM, a RAT/user, etc. regarding the requested service. A network slice as referred to herein may indicate bandwidth, network resources, and the like. Enablement module 110 provides recommendations based on network parameters such as, but not limited to, round-trip time between UE 102 and an application server, end-to-end (E2E) delay, network level, and the like. Thus, the best possible suggestion may be provided to the user to complete the service, which may improve the user experience in terms of throughput, delay and cost impact. In another embodiment, based on a set user priority (including cost-effective factors, performance factors, best effort factors, etc.), enablement module 110 can use the determined recommendations to complete the service.

In another embodiment, the cloud server 116 (as shown in fig. 1 b) may also provide recommendations to the user for completing the service at a particular location if the edge server provider (of the edge servers (106 a-106 n)) does not comply with the ETSI standard. The cloud server 116 continuously receives parameters such as, but not limited to, operator network, availability of edge servers, network slice characteristics, RTT, signal strength, geographic location, etc., from the enablement module 110 of the UE 102. The cloud server 116 analyzes the received parameters using a machine learning model and determines at least one of the availability of the edge server, the availability of the application server, the RAT for the application, etc. to complete the user request service. In response to the query received from the enablement module 110, the cloud server 116 provides the recommendation to the enablement module 110.

In an embodiment, if the edge server provider complies with the ETSI standard, the UE 102 may use a well-defined Application Programming Interface (API) interface to determine available services running on the edge servers (106 a-106 n).

The display module 114 may be configured to display the recommendations determined by the enablement module 110 on a display screen of the UE 102.

The communication interface module 112 may be configured to establish a connection between the UE 102 and at least one of an application server, an edge server, and the like. The communication interface module 112 may operate according to the function of the connection layer.

The memory 108 may include applications, information about recommended applications, information about network resources, network parameters, and the like. Memory 108 may include one or more computer-readable storage media. The memory 108 may include non-volatile storage elements. Examples of such non-volatile storage elements may include magnetic hard disks, optical disks, floppy disks, flash memory, or forms of electrically programmable memories (EPROM) or Electrically Erasable and Programmable (EEPROM) memories. Additionally, in some examples, the memory 108 may be considered a non-transitory storage medium. The term "non-transitory" may indicate that the storage medium is not embodied in a carrier wave or propagated signal. However, the term "non-transitory" should not be construed to mean that the memory 108 is not removable. In some examples, the memory 108 may be configured to store a greater amount of information than memory. In some examples, a non-transitory storage medium may store data (e.g., in Random Access Memory (RAM) or cache) that may change over time.

Fig. 1a and 1b illustrate elements of a communication system 100, but it should be understood that other embodiments are not so limited. In other embodiments, communication system 100 may include a fewer or greater number of elements. Furthermore, the labels or names of the elements are for illustration purposes only and do not limit the scope of the embodiments herein. One or more elements may be combined together to perform the same or substantially similar functions in communication system 100.

Fig. 2 is an example block diagram illustrating various elements of an enabling module 110 for providing recommendations to complete a service by a UE 102 in accordance with embodiments disclosed herein. The enablement module 110 includes an edge tracker unit 202, an edge availability based recommendation unit 204, a query based recommendation unit 206, a network slice selector unit 208, a profile selector unit 210, a quality of service (QoS) manipulation unit 212, and a resource optimizer based recommendation unit 214.

The edge tracker unit 202 may be configured to determine the availability of edge servers (106 a to 106 n) of the UE 102 during a start-up operation (which may include the UE 102 starting up, the UE 102 exiting an airplane mode, etc.) or upon determining a change in cell location. In an embodiment, the edge tracker unit 202 uses ETSI MEC criteria to determine the availability of edge servers. The edge tracker unit 202 sends a "registration request" to the 5G core network to check the availability of the edge servers (106 a to 106 n). In response to the "registration request," the edge tracker unit 202 receives a "registration accept" response from the 5G core network indicating the availability of the edge servers (106 a to 106 n). Upon determining that the edge servers (106 a-106 n) are available, the edge tracker unit 202 also verifies the availability of the edge servers (106 a-106 n) by checking system attributes of the UE 102.

Upon determining that an edge server (106 a-106 n) is available, the edge tracker unit 202 instructs the display module 114 to update a status bar displayed on the screen of the UE 102. The updated status bar may indicate to the user the availability of the edge servers (106 a-106 n). In examples herein, the display module 114 may display a letter/icon "M" on the status bar to indicate the availability of the edge servers (106 a-106 n). Embodiments are explained herein in view of displaying an icon "M" on the status bar to indicate availability of the edge server, but any suitable display indication is contemplated.

Upon determining that the edge servers (106 a-106 n) are available, the edge tracker unit 202 queries the edge service provider for availability of one or more applications by sending a query command to the edge servers (106 a-106 n). In the examples herein, the edge tracker unit 202 queries the edge service provider for the availability of one or more applications by sending a "get application list" command to the edge servers (106 a to 106 n). In response to the query command, the edge tracker unit 202 obtains a response from the edge service provider, wherein the response provides information about the availability of one or more application server instances at the edge servers (106 a to 106 n). In examples herein, the response received from the edge server (106 a-106 n) may be in a hypertext transfer protocol (HTTP) response format. Further, the edge tracker unit 202 instructs the display module 114 to provide notifications for one or more applications residing on the UE 102 based on the availability of the edge servers (106 a-106 n) for the one or more applications.

Upon receiving instructions from the edge tracker unit 202, the display module 114 performs a User Interface (UI) based action. UI based actions may be, but are not limited to, providing badge notifications, creating folders, etc. In an embodiment, upon receiving instructions from the edge tracker unit 202, the display module 114 creates a folder and inserts one or more applications available at the edge servers (106 a-106 n) into the created folder. In examples herein, upon receiving instructions from the edge tracker unit 202, the display module 114 creates a MEC folder and inserts one or more applications available at the edge servers (106 a-106 n) into the MEC folder.

In another embodiment, upon receiving instructions from the edge tracker unit 202, the display module 114 assigns a badge notification for one or more applications available at the edge servers (106 a-106 n). The badge notification may include one or more letters indicating the availability of the edge servers (106 a-106 n) for one or more applications. In examples herein, assigning a badge notification may include assigning the letter "M" to one or more applications available at the edge servers (106 a-106 n). The embodiments explained herein contemplate assigning the letter "M" to an indication of the availability of an edge server or application, but any other suitable display indication may be considered.

The edge tracker unit 202 may be further configured to determine availability of local storage suitable for the edge servers (106 a to 106 n) to upload content. The local storage may be, but is not limited to, a file server, network Attached Storage (NAS), local cloud, and the like. The edge tracker unit 202 determines availability of a local storage adapted to the edge servers (106 a to 106 n) while retrieving a list of available applications on the edge servers (106 a to 106 n). The edge tracker unit 202 determines the availability of local storage employed by the edge servers (106 a to 106 n) according to ETSI standards.

In determining the availability of local storage employed by the edge servers (106 a-106 n), the edge tracker unit 202 can delegate the task of downloading content to the edge servers (106 a-106 n), and can later download the content upon determining that the user is moving. In examples herein, content (e.g., files) stored in a local store may be viewed using a file browser installed using the Web distributed authoring and versioning protocol (WebDAV protocol). Content stored in the local storage may also be streamed from the edge servers (106 a-106 n) when a user performs a gesture (e.g., a click, a tap, a swipe, etc.) on the content. Thus, the use of device storage may be reduced.

The edge availability-based recommendation unit 204 may be configured to recommend one or more applications to fulfill the user request service. The edge availability based recommendation unit 204 may also recommend applications for the currently used RAT. A service may be recommended for the application based on at least one of a Round Trip Time (RTT) and an end-to-end (E2E) delay.

When a request for the first service is received from the user at a specific location, the edge availability-based recommending unit 204 recommends an application to complete the first service based on the RTT. The first service may be a throughput-based service and not include any call-related services. Examples of the first service may be, but are not limited to, a streaming service, a file download service, a carousel service, and the like.

The edge availability based recommender unit 204 determines an RTT between the UE 102 and the application server for one or more applications supporting the requested service. The application server may be a server supporting one or more applications for the requested first service. The application servers herein may reside in the edge servers (106 a-106 n). In embodiments, the RTT may be determined using any suitable application compatible with an Operating System (OS) of the UE 102. In another embodiment, the RTT may be determined based on a time difference measured for packets arriving from the UE 102 at the application server, or vice versa. It should be noted that the embodiments herein are not limited to the above-described method for measuring RTT, and that RTT may be measured using any other technique/method without hampering the intended functionality of the features of the embodiments that can be inferred from this description.

The edge availability based recommender unit 204 determines RTTs for one or more applications based on each of a plurality of cells associated with a base station (104 a-104 n) with which the UE 102 is communicating. The edge availability based recommender 204 averages the calculated RTTs for one or more applications. The edge availability-based recommending unit 204 selects an application having the lowest RTT value from among the one or more applications to complete the requested first service. The average RTT value may vary depending on parameters such as, but not limited to, availability of edge services, network slicing characteristics, signal strength for a particular geographic location, current network load, etc. Further, the application with the lowest RTT value indicates that the application is available on the edge server (106 a to 106 n). Edge servers (106 a-106 n) may be deployed near base stations (104 a-104 n) that communicate with UE 102. Thus, the applications available on the edge server may be the best possible applications to complete the service at a particular location, thereby enabling low latency communication.

For example, consider a scenario in which a user requests a video streaming service at a particular location, and applications (apps) a, B, and C are certain applications that support the video streaming service. The edge availability-based recommendation unit 204 determines RTTs (104 a to 104 n) for app a, app B, and app C on a per cell basis of the base station, and averages the determined RTTs for app a, app B, and app C. The edge availability based recommender 204 determines that app a has the lowest RTT value. Further, based on the RTT value, the edge availability-based recommender 204 identifies that app a is available on the edge servers (106 a-106 n). Accordingly, the edge availability-based recommender 204 suggests app a to complete the video streaming service at a particular location.

Further, upon receiving a request from the second service, the edge availability-based recommendation unit 204 recommends an application for the second service based on the E2E delay. Examples of the second service may be a call related service, a conference related service, and the like. The edge availability based recommendation unit 204 determines an E2E delay for one or more applications supporting the second service. The E2E delay (also referred to as mouth-to-ear delay) determined for one or more applications may be the latency between the MO (mobile initiator) 102 and the MT (mobile terminator) (104 a to 104 n). The E2E delay may be a delay that refers to the time it takes to send a packet from the MO 102 to the MT (104 a to 104 n) through the Radio Access Network (RAN). The edge availability based recommendation unit 204 determines an E2E delay based on each of a plurality of cells associated with base stations (104 a-104 n) that are further in communication with the UE 102. The edge availability based recommender 204 averages the calculated E2E delays for one or more applications. The edge availability based recommendation unit 204 selects the application with the lowest E2E value from the one or more applications to complete the requested second service. The average E2E delay value may vary depending on parameters such as, but not limited to, availability of edge services, network slice characteristics, signal strength at a particular geographic location, location of the MT, current network load, etc. Further, the application with the lowest E2E delay value indicates that the application is available at an edge server (106 a-106 n) deployed near a base station (104 a-104 n) in communication with the UE 102. Thus, applications available at the edge servers (106 a to 106 n) may be recommended as the best possible applications for completing the service at a specific location, thereby enabling low latency communication.

For example, consider an example scenario in which a user wants to call another user, and app C1, app C2, and app C3 are certain applications that support call-related services. The edge availability-based recommender unit 204 determines the E2E delays for apps C1, C2, and C3 and averages the determined E2E delays for apps C1, C2, and C3. The edge availability based recommender 204 determines that the E2E latency of app C2 is low. Since app C2 has the lowest E2E latency, app C2 can be used on the edge servers (106 a to 106 n). Thus, the edge tracker unit 202 suggests app C2 to a user who can call another user using app C2.

The edge availability based recommender unit 204 instructs the display module 114 to display a recommendation application (based on at least one of RTT and E2E delay) to the user to complete the requested service. In another embodiment, based on the set user priority, the edge availability recommendation unit 204 may automatically switch to a recommendation application to complete the service.

The query-based recommendation unit 206 may be configured to query the cloud server 116 and recommend an application to complete a service at a particular location. When a request to complete a service (including at least one of the first service and the second service) is received from a user, the query-based recommendation unit 206 sends the request to the cloud server 116. The request may include at least one of a cell identifier, an operator network identifier, a geographic location, and the like. The query may be for availability of the edge server and the application supporting the requested service. In response to the request, the query-based recommendation unit 206 receives a recommendation from the cloud server 116 to complete the requested service at the particular location. The recommendation may be at least one of an availability of the edge server, an application for completing the requested service, a RAT for the application, and the like. The query-based recommendation unit 206 instructs the display module 114 to display a recommendation to the user for completing the requested service.

For example, consider an example scenario in which a user wants to watch a movie, and app a, app B, and app C are available applications on the UE 102 that support video/movie streaming related services. The query-based recommendation unit 206 queries the edge service provider and recommends app C for watching the movie based on the availability of the edge servers (106 a to 106 n) of app C.

The slice selector unit/network slice selector unit 208 may be configured to select a network slice of SIMs present in the UE for completing the requested service at a particular location. The network slice selector unit 208 may select a network slice for a SIM based on factors such as availability of network slices, characteristics of available network slices, and so on. The network slice may be characterized by, but is not limited to, throughput, latency, etc. In an embodiment, the network slice selector unit 208 provides an automatic mode and a user mode for selecting at least one of a SIM for a requested service and a network slice of the SIM.

In the automatic mode, the network slice selector unit 208 selects a network slice according to the single-slice selection assistance information (S-NSSAI) of the 3GPP standard. The network slice may be selected based on its behavior in terms of functionality and service. In the automatic mode, the network slice selector unit 208 may also select a network slice based on a preconfigured user priority. The user priority may be based on at least one of a cost benefit factor, a performance factor, a best effort factor, and the like.

In user mode, the user may be provided with the option of selecting at least one of a network slice, a SIM, etc. Each option may include details regarding the availability of the edge servers (106 a-106 n) for the particular service selected. Further, the network slice selector unit 208 may obtain information for the user-selected network slice by initiating a Protocol Data Unit (PDU) session setup with an access and mobility management function (AMF) instance serving the UE 102. The information obtained for the network slice may be at least one of a Data Network Name (DNN), a Session and Service Continuity (SSC) pattern, a session type, and the like. In addition, the network slice selector unit 208 may provide an interface to the user to request new network slices for the requested service as needed.

The profile selector unit 210 may be configured to track RATs associated with base stations communicating with the UE 102 and subscriptions associated with charging details. Subscription and charging details may be tracked based on a summary of the SIM downloaded to the UE 102. Further, the summary selector unit 210 may provide the user with an interface for purchasing/editing subscriptions and downloading the corresponding summaries of the subscriptions to the SIM. Profile selector unit 210 uses 5G features such as, but not limited to, resource class, priority, packet Delay Budget (PDB), packet Error Rate (PER), averaging window, maximum data burst size, and the like, and recommends RAT/subscription to fulfill the user request service.

The QoS manipulator unit 212 may be configured to prioritize the traffic of the applications by manipulating the QoS for different characteristics of the applications. The QoS manipulator 212 prioritizes traffic for the application(s) that is not available on the edge servers (106 a to 106 n). To prioritize the traffic for a particular application, the QoS manipulator 212 provides a 5G QoS identifier (5 QI) for that application and sends the 5QI value further to the RAT to provide better bandwidth and latency for such application.

The resource optimizer-based recommendation unit 214 may be configured to provide recommendations for completing services at specific locations based on network levels. The recommendation may be at least one of an application, RAT, SIM, etc. for completing the service. When the UE 102 supports multiple SIMs, the resource optimizer-based recommendation unit 214 determines a network class for each SIM.

Resource optimizer-based recommender unit 214 communicates with edge tracker unit 202, edge availability-based recommender unit 204, network slice selector unit 208, profile selector unit 210 and QoS manipulator unit 212 and obtains information about the availability of edge servers (106 a to 106 n), RTT and E2E delays, availability/selection of network slices/SIMs, RATs and associated subscriptions and charging details and QoS for the application operation. Using this information, resource optimizer-based recommender unit 214 determines a network rank. A network class may be computed for at least one of a subscription/RAT, an application, a SIM, and the like. In addition, resource optimizer-based recommendation unit 214 uses the received information (e.g., without limitation, RAT/subscription, availability of edge servers and network slices, corresponding QoS, charging details for subscription/RAT, RTT, E2E delay, etc.) to update a local database corresponding to one or more applications. Thus, the resource optimizer-based recommendation unit 214 may provide the best possible recommendation based on at least one of the network ratings and using the information of the updated database.

Based on the network levels computed for one or more applications supporting the requested service, the resource optimizer-based recommendation unit 214 recommends an application for the requested service. Based on the network rank calculated for the one or more RATs associated with the UE 102, the resource optimizer-based recommendation unit 214 recommends the RATs available for the application recommended for the requested service. Further, the resource optimizer-based recommendation unit 214 recommends SIMs that are available for the application recommended for the requested service based on at least one of characteristics of available network slices for the SIMs and network levels determined for one or more SIMs. In addition, the resource optimizer-based recommendation unit 214 recommends a network slice for the SIM based on at least one of the characteristics of the available network slices for the SIM.

Further, the network level may be expressed as a function of parameters such as, but not limited to, signal strength, network load information, network slice availability, edge availability, RTT, and the like. The network rank may be calculated as follows:

NWR＝f2(S,E,RTT*,C,X)

where f2 represents a function value, 'S' represents availability of a network slice/network slice rating, 'E' represents availability of an edge rating of an edge service/service, 'C' represents a function of signal strength and network load based on charging detail information, 'X' represents a function of signal strength and network load. "X" can be expressed as: x = f1 (SS, NL)

Where "f1" represents the function value, "SS" represents the signal strength, and "NL" represents the network load. The "X" rating is better if both the signal strength and the network rating are good. Furthermore, the availability of high throughput and low latency network slices may increase the network tier as compared to network slices with only one or no of them. Further, calculating a network rank using the RTT may be considered only when the network slice and the edge servers (106 a-106 n) are unavailable.

In addition, the network rank may be calculated as

NWR＝W1*SS+W2*C+W3*NL+W4*E+W5*S

Where W1 to W5 represent weights provided based on the availability and network slice of the edge servers (106 a to 106 n), signal strength thresholds, billing thresholds, RTT thresholds, network load, etc. Based on the network level, the resource optimizer-based recommendation unit 214 may provide recommendations for completing the requested service. The resource optimizer-based recommendation unit 214 instructs the display module 114 to display a recommendation to the user to complete the service at a particular location. For example, consider a scenario in which a user wants to watch a live football game, and app a and app B may be determined to be applications that support streaming of the live football game. Resource optimizer-based recommendation unit 214 determines the network levels of app a and app B and identifies that app B has a network level greater than app a. Accordingly, the resource optimizer-based recommending unit 214 recommends app B to the user watching the live soccer game.

Further, based on the network optimizer, the resource optimizer-based recommendation unit 214 recommends at least one of an application and a SIM for completing a service based on factors such as, but not limited to, performance factors, cost effectiveness.

In the case of providing recommendations based on performance factors, the resource optimizer-based recommendation unit 214 provides recommendations for completing services regardless of billing detail information. Recommendations may be provided by considering the availability of edge servers and network slices, signal strength, and network load. In the examples herein, for an autonomous driving application, the resource optimizer-based recommendation unit 214 may provide recommendations based on performance factors. In the case of providing recommendations based on cost-effectiveness factors, the resource optimizer-based recommendation unit 208 takes into account the billing parameters and provides recommendations, regardless of other parameters. In the examples herein, the resource optimizer-based recommendation unit 214 may provide recommendations based on cost-benefit factors when the user wants any service without any fees. In an embodiment, the resource optimizer-based recommendation unit 214 may instruct the display module 114 to provide an interface to the user and receive information from the user regarding a selection of at least one of performance factors and cost benefit factors for providing recommendations.

Fig. 2 shows the elements of the enablement module 110, but it is understood that other embodiments are not so limited. In other embodiments, the enablement module 110 may include a fewer or greater number of cells. Furthermore, the labels or names of the elements are for illustration purposes only and do not limit the scope of the embodiments herein. One or more units may be combined together to perform the same or substantially similar functions in the enablement module 110.

Fig. 3 is a flow chart 300 illustrating a method for providing recommendations to complete a service of a UE at a particular location according to embodiments disclosed herein.

At step 302, the method includes: the enablement module 110 determines the network parameter in response to a request received from a user for at least one service at the location. The network parameter may be, but is not limited to, at least one of: availability of edge servers, RTT and E2E delays, availability of network slices, characteristics of available network slices, network load, billing details, signal strength, etc.

At step 304, the method includes executing, by the enablement module 110, the service by determining a recommendation based on the determined network parameter. The recommendation may be at least one of an application for performing the requested service, a SIM, a network slice of a SIM, a RAT/subscription, etc. In addition, the recommendation may include an application for the RAT currently in use. In an embodiment, based on the user priority setting, the enablement module 110 may automatically use the recommendation to complete the requested service. In another embodiment, the enablement module 110 may provide the determined recommendation to the user to perform the requested service.

The various actions, operations, blocks, steps, etc., in this method and flowchart 300 may be performed in the order presented, in a different order, or simultaneously. Further, in some embodiments, some acts, operations, blocks, steps, etc. may be omitted, added, modified, skipped, etc. without departing from the scope of the present disclosure.

Fig. 4a is a flow chart 400A illustrating a method for recommending an application for completing a particular service of a UE at a particular location based on at least one of RTT and E2E delay, according to embodiments disclosed herein.

At step 402, the method includes calculating, by the enablement module 110, at least one of an RTT and an E2E delay for one or more applications supporting the user requesting the service. The requested service may include at least one of a first service (e.g., a streaming service, a file download service, a carousel service, etc.) and a second service (e.g., a call-related service). The enablement module 110 calculates an RTT for one or more applications supporting the first service and an E2E delay for one or more applications supporting the second service. The enabling module 110 calculates at least one of an RTT and an E2E delay based on each of a plurality of cells of a base station (104 a-104 n) in communication with the UE 102. Further, the enablement module 110 averages at least one of RTT and E2E delay for one or more applications that support the requested service.

At step 404, the method includes: the enablement module 110 recommends an application from the one or more applications for completing the requested service based on at least one of the calculated RTT and the E2E delay. The enablement module 110 selects an application from the one or more applications that has at least one of a lowest RTT value and a lowest E2E delay. The enablement module 110 recommends the selected application as a recommended application for completing the requested service.

The various actions, operations, blocks, steps, etc., in this method and flowchart 400A may be performed in the order presented, in a different order, or simultaneously. Further, in some embodiments, some acts, operations, blocks, steps, etc. may be omitted, added, modified, skipped, etc., without departing from the scope of the present disclosure.

Fig. 4B is a flow chart 400B illustrating a method for providing recommendations for a service by querying the service deployed on the cloud 116, according to embodiments disclosed herein.

At step 406, the method includes receiving, by the cloud server 116 (a service deployed on the cloud server 116), parameters for one or more applications supporting the service from the enablement module 110 of the UE 102 on the cell. The parameters may be, but are not limited to, operator network, availability of edge servers, network slice characteristics, RTT, signal strength, geographical location, etc.

At step 408, the method includes analyzing, by the cloud server 116, the parameters received from the enablement module 110 using a machine learning model to determine an application for the service from the one or more applications. At step 410, the method includes recommending, by cloud server 116, the determined application available for use in completing the service on UE 102 after receiving the request from enablement module 110. The request may include at least one of a cell ID, a tower ID, a geographic location, and the like. Accordingly, enablement module 110 may query cloud server 116 to recommend an application for completing the requested service at a particular location.

The various actions, operations, blocks, steps, etc. in this method and flowchart 400B may be performed in the order presented, in a different order, or simultaneously. Further, in some embodiments, some acts, operations, blocks, steps, etc. may be omitted, added, modified, skipped, etc., without departing from the scope of the present disclosure.

FIG. 4C is a flowchart 400C illustrating a method for providing recommendations for a requested service based on network ratings according to embodiments disclosed herein.

At step 412, the method includes determining, by the enablement module 110, a network level upon receiving a request from a user to complete a service. A network rank may be calculated for at least one of one or more applications supporting the requested service, one or more RATs associated with the base stations (104 a-104 n), one or more SIMs, and the like. The network tier may be calculated based on parameters such as, but not limited to, signal strength, network load information, network slice availability, edge availability, RTT, etc. The network rank (NWR) may be calculated as follows:

NWR＝W1*SS+W2*C+W3*NL+W4*E+W5*S

at step 414, the method includes providing, by the enablement module 110, a recommendation for completing the requested service. Recommendations may be, but are not limited to, applications, SIMs, RATs, network slices of SIMs, etc.

In embodiments, the enablement module 110 can recommend an application for a requested service based on a network level determined for one or more applications supporting the requested service. In another embodiment, the enablement module 110 may suggest a RAT for the application recommended for the requested service based on the determined network class for one or more RATs. In yet another embodiment, based on the network class determined for one or more SIMs, enablement module 110 may suggest the SIM for an application recommended for the requested service. In yet another embodiment, the enablement module 110 suggests a network slice for the SIM for the application recommended for the requested service based on at least one of the network slice characteristics and the network class determined for the one or more SIMs.

The various actions, operations, blocks, steps, etc., in this method and flowchart 400C may be performed in the order presented, in a different order, or simultaneously. Further, in some embodiments, some acts, operations, blocks, steps, etc. may be omitted, added, modified, skipped, etc., without departing from the scope of the present disclosure.

Fig. 5a, 5b, and 5c are example diagrams illustrating a recommendation of an application for a requested service based on RTT according to embodiments disclosed herein.

Consider a scenario as shown in fig. 5a, where a user wants to watch a video, and app a, app B, app C, and app D are applications that support video-streaming related services. Enablement module 110 determines RTTs for app a, app B, app C, and app D. The RTT may be calculated based on each of a plurality of cells associated with base stations (104 a-104 n) with which the UE 102 communicates. In the example herein, the RTT may be calculated based on a cell with a cell identifier (cid) of 400, a cell with a cid of 500, and a cell with a cid of 600 (serving cell) of the base stations (104 a to 104 n). Since the edge servers (106 a to 106 n) are placed in the vicinity of the base stations (104 a to 104 n) serving the cell of cid 500, applications may be recommended taking into account the RTT calculated based on the cell of cid 500. The RTTs calculated for app a, app B, app C and app D based on the cid 500 cell may be 20ms, 16ms, 25ms and 15ms, respectively. Thus, enablement module 110 identifies that edge servers (106 a-106 n) are available for app D. Thus, since app D has the lowest RTT value, the enablement module 110 recommends app D for viewing the video. Therefore, communication with low latency can be achieved.

Consider an example scenario as shown in fig. 5b, where a user searches for a movie to stream. Enablement module 110 determines that app a, app B, app C, and app D are applications that support video stream/movie related services. The enabling module 110 calculates an RTT for an application supporting the video streaming service. In the examples herein, the RTTs computed for app a, app B, app C, and app D may be 20ms, 15ms, 25ms, and 5ms, respectively. Accordingly, enablement module 110 recommends app D for viewing the movie because app D has the lowest RTT value.

As shown in fig. 5c, the user starts the video streaming service. The enablement module 110 determines from the one or more applications that the application has the lowest RTT value. Once the application is determined, the enablement module 110 provides a suggestion for the user to continue the initiated service using the determined application (with the lowest RTT value).

Fig. 6a and 6b are example diagrams illustrating recommendation of applications for call related services based on E2E delay according to embodiments disclosed herein.

Consider an example scenario as shown in fig. 6a, where a user wants to call another user, and app C1, app C2, app C3, and app C4 are applications that support call-related services. Upon receiving a request from a user for call-related services, enablement module 110 calculates an E2E delay for apps C1-C4 based on each of a plurality of cells of a base station in communication with UE 102 (cell of cid 400, cell of cid 500, and cell of cid 600). In the example herein, the E2E delays calculated for app a, app B, app C and app D based on the cid 500 cell may be 20ms, 5ms, 25ms and 15ms, respectively. Since app C2 has the lowest E2E latency, enablement module 110 identifies the availability of edge servers (106 a-106 n) for app C2. Accordingly, enablement module 110 recommends app C2 to the user to place a call to another user.

As shown in fig. 6b, the user makes an OTT app call. The enablement module 110 selects an OTT app based on the lowest E2E delay and provides a suggestion to the user to continue calling on the selected OTT app.

Fig. 7 is an example diagram illustrating a recommended application of a particular service by a service deployed on cloud server 116 according to embodiments disclosed herein. Consider an example scenario as shown in fig. 7, where a user wants to watch a movie and apps a-D are available on a UE that supports movie formats/streams. Enablement module 110 of UE 102 queries cloud server 116 to suggest that the application watch the movie. The cloud server 116 determines an application for watching a movie based on the parameters/5G characteristics continuously received from the UE 102 on at least one cell (which may be a cell with a cid of 400, 500, and 600) of the base station (104 a to 104 n) in communication with the UE 102. The parameters may be, but are not limited to, operator network, edge availability, network slice characteristics, RTT, signal strength, location details, etc. In the example herein, based on the received parameters, the edge servers (106 a to 106 n) determine that the edge servers are placed near a base station serving the cell of cid 500. Further, the cloud server 116 determines that app C is the only available application on the edge servers (106 a-106 n) that supports the movie-related service. The servers (106 a-106 n) provide app C as a suggestion in response to the request received from the enablement module 110. Thus, enablement module 110 recommends app C to the user as the best possible application to watch the movie.

Fig. 8 is an example sequence diagram illustrating determining availability of an edge server for one or more applications according to embodiments disclosed herein. As shown in fig. 8, during a startup operation (which may include UE 102 starting up, UE 102 exiting flight mode, etc.) or during a determination of a change in cell location, enable module 110 of the UE checks the availability of the edge server. Furthermore, the enabling module 110 sends a "registration request" to the 5G core network using the modem to check whether the edge servers (106 a to 106 n) are available. In response to the "registration request", the 5G core network sends a "registration request" to the modem.

The radio interface layer of the UE 102 determines the availability of the edge servers (106 a to 106 n) based on the "registration accept" response received from the 5G core network. The enablement module 110 uses system attributes of the UE 102 to verify the availability of the edge servers (106 a-106 n). Upon determining that edge servers (106 a-106 n) are available for a base station to communicate with UE 102, enablement module 110 updates a status bar on UE 102 indicating the availability of the edge servers.

Further, the enablement module 110 queries a lifecycle management (LCM) agent associated with the 5G core network to obtain information about a list of applications available on the edge servers (106 a-106 n). The LCM agent may send a list of available applications at the edge servers (106 a-106 n) to the enablement module 110. The enablement module 110 assigns the indication/badge notification to the applications available on the edge servers (106 a-106 n).

9a, 9b, and 9c are exemplary diagrams illustrating the creation of a folder structure for indicating the availability of edge servers (106 a-106 n) for one or more applications according to embodiments disclosed herein; the enablement module 110 instructs the display module 114 to update the status bar when determining the availability of the edge servers (106 a-106 n). In the examples herein, the display module 114 notifies the user of the availability of the edge server via an "M" letter/icon on the status bar. In addition, the display module 114 creates MEC folders and inserts one or more applications available on the edge server into the created folders.

In the case of a single SIM, the display module 114 creates a folder containing one or more applications supported on the edge servers (106 a-106 n), as shown in fig. 9 a.

In the case of multiple SIMs, the display module 114 creates a folder with respect to the SIMs and inserts applications available at the respective edge servers (106 a to 106 n) into the folder, as shown in fig. 9b and 9 c. In an example herein, the folders created with respect to SIM1 may include apps a through E available on edge servers (106 a through 106 n). In examples herein, the folders created with respect to SIM2 may include app a and app B supported on edge servers (106 a to 106 n).

Fig. 9d is an example diagram illustrating the allocation of badge notifications for one or more applications available at the edge servers (106 a-106 n) according to embodiments disclosed herein. In examples herein, the letter "M" may be added to an application to indicate the availability of an edge server (106 a-106 n) to the application. The letter "M" may be assigned to apps E and F to inform the user about the availability of the edge servers (106 a-106 n) of apps E and F.

Fig. 9e is an example diagram illustrating providing a user notification for indicating availability of an edge server (106 a-106 n) according to embodiments disclosed herein. After initiating operations (which may include UE 102 starting, UE 102 exiting airplane mode, etc.), enablement module 110 determines the availability of the edge servers using a 5G registration procedure (106 a-106 n) and receives a list of available applications from the LCM agent. The enablement module 110 instructs the display module 114 to create a folder to insert or provide a badge notification to an application available on an edge server (106 a-106 n). In the examples herein, the user selects app E (available on the edge server) based on at least one of a badge notification and a folder. Upon selection of app E, the user may be provided with an interface to select a network slice of the SIM card during application launch. For example, the user may select network slice 1 of the SIM based on latency. Thus, after launching the application, the user can manage app E using network slice 1 of SIM1.

Fig. 10 depicts an example diagram in which a local store is adapted with an edge server for uploading content according to embodiments disclosed herein. Embodiments herein enable the enablement module 110 to notify the user of local storage adapted to the edge servers (106 a-106 n). Thus, the user can delegate the task of downloading content (files, videos, photos, etc.) to a local cloud that is adapted to the edge server. In addition, the user can share information about the uploaded content with other users. The user may also obtain downloaded content from the edge server, which helps to reduce the use of device storage. Thus, utilizing edge servers (106 a-106 n) to adapt local clouds helps to increase storage capacity and provide a seamless content sharing experience.

11 a-11 h depict example tables in which the table values may be used to determine a network rank according to embodiments disclosed herein. The enablement module 110 of embodiments herein is capable of recommending at least one of an application, a RAT, a SIM, and a network slice of the SIM for a particular service at a particular location based on a network tier. The network rank (NWR) may be determined based on network parameters such as, but not limited to, signal strength, network load information, network slice availability, edge availability, RTT, and the like. The network rank may be calculated as follows:

NWR＝W1*SS+W2*C+W3*NL+W4*E+W5*S

where W1 to W5 represent weights considered based on at least one of a signal strength threshold, a charging threshold, an RTT threshold, a network load, availability of edge servers and network slices, and the like. Typical values for the range of network parameters are shown in fig. 11a to 11 h.

Fig. 12 is an example flow diagram illustrating a recommendation of a RAT to complete requested service at a particular location based on network class according to embodiments disclosed herein. Consider an example scenario in which app a has started to support a video streaming service. Enablement module 110 checks whether UE 102 supports multiple SIMs. Upon determining that UE 102 does not support multiple SIMs, enablement module 110 suggests to the user to continue with the session for app a.

Upon determining that UE 102 supports multiple SIMs, enablement module 110 determines network classes of one or more RATs/subscriptions supported by a base station (104 a-104 n) in communication with UE 102. The enablement module 110 selects a RAT from the one or more RATs based on the network class to complete the video streaming service. In an embodiment, the enablement module 110 may select a RAT upon receiving an input from a user to complete a video streaming service. Further, the enablement module 110 suggests to the user to continue the video streaming service on the selected RAT. In examples herein, the one or more RATs supported by the base station communicating with the UE 102 may be LTE, 5G, and Wi-Fi. The enablement module 110 calculates the network classes for LTE, 5G, and Wi-Fi and identifies that 5G may have a better network class. Thus, the enablement module 110 recommends 5G as the best RAT for continuing the video streaming service.

Fig. 13 is an example table illustrating network slices for an edge server/SIM recommending an application for a requested service at a particular location according to embodiments disclosed herein. Consider an example scenario in which a user is watching a live event, and app a and app B are applications that support live event streaming. The enablement module 110 determines the network level of apps a and B based on parameters such as, but not limited to, signal strength, network load information, RTT, availability of edge servers and network slices, billing details, and the like. Example values of parameters for app a and app B are shown in the table. The Network Rating (NRA) calculated for app a using example values of parameters associated with app a may be:

NRA =0.15 × 5 (signal strength) +0.1 × 4 (billing) +0.15 × 1 (network load) +0 (edge) +0 (network slice) =1.3

Similarly, the Network Rating (NRB) calculated for app B using an example value of a parameter associated with app B may be:

NRB =0.15 × 5 (signal strength) +0.1 × 3 (billing) +0.15 × 1 (network load) +1 × 0.3 (edge) +1 × 0.3 (network slice) =1.8

The enablement module 110 determines that the network level computed for app B may be higher than that of app a. The network level of app B may be higher due to the availability of edge servers and network slices. Thus, even if the billing details associated with app a are low, the enablement module 110 selects app B for viewing the live event based on performance factors.

Fig. 14a and 14b depict example tables in which the values of the example tables are used to recommend a SIM for a requested service at a particular location according to embodiments disclosed herein. Consider an example scenario in which a user wants to watch a video, and app a may be recommended for video streaming. Further, UE 102 includes SIM1 and SIM2, which support app a. The enablement module 110 determines the network tier of

SIMs

1 and 2 based on parameters such as, but not limited to, signal strength, network load information, RTT, availability of edge servers and network slices, billing details, and the like. Example values of the parameters with respect to SIM1 and SIM2 are shown in the table shown in fig. 14 a. The network level (NR 1) calculated for SIM1 using example values of parameters associated with SIM1 may be:

NR1=0.05 × 5 (signal strength) +0.7 × 4 (billing) +0.05 × 1 (network load) +1 × 0 (edge) +0 (network slice) =3.1

Similarly, the network level (NR 2) calculated for SIM2 using example values of parameters associated with SIM2 may be:

NR2=0.05 × 5 (signal strength) +0.7 × 3 (billing) +0.05 × 1 (network load) +0 (edge) +1 × 0.1 (network slice) =2.5

Enablement module 110 determines that the network class computed for SIM1 may be higher than SIM2. Thus, even if SIM2 has a network slice, enablement module 110 selects SIM1 for app a (supporting video streaming services) based on cost-benefit factors.

Consider an exemplary auto-drive automotive example where performance/delay is prioritized over cost. Further, app B supports an automatic driving-related service. The enablement module 110 determines the network level of SIM1 and SIM2 based on parameters such as, but not limited to, signal strength, network load information, RTT, availability of edge servers and network slices, billing details, and the like. Example values of the parameters with respect to SIM1 and SIM2 are shown in the table as shown in fig. 14 b. The network level (NR 1) calculated for SIM1 using example values of parameters associated with SIM1 may be:

NR1=0.15 × 5 (signal strength) +0.1 × 5 (billing) +0.15 × 1 (network load) +0 (edge) +0 (network slice) =1.4

NR2=0.15 × 5 (signal strength) +0.1 × 3 (billing) +0.15 × 1 (network load) +1 × 0.3 (edge) +1 × 0.3 (network slice) =1.8

Enablement module 110 determines that the network class computed for SIM2 may be higher than SIM1. Thus, even though less billing detail information is associated with SIM1, enablement module 110 selects SIM2 (which supports autopilot-related services) for app B based on performance factors.

Fig. 15a and 15b are example diagrams illustrating a recommendation of a SIM for a requested service at a particular location according to embodiments disclosed herein. Consider an example scenario as shown in fig. 15a, where a user wants to watch a movie, and app a, app B, app C, and app D may be applications available on a UE 102 that supports video/movie streaming services. Further, enablement module 110 recommends app a for viewing a movie on UE 102 at a particular location.

Further, UE 102 supports SIM1 of operator 1 and SIM2 of operator 2. The serving cell of cid 500 of the base station communicating with UE 102 may be operated by operator 1 and operator 2. Thus, enablement module 110 determines the availability of edge servers (106 a-106 n) for base stations (communicating with UE 102) with respect to operator 1 and operator 2.

In the examples herein, edge servers (106 a-106 n) are available for SIM1 operated by operator 1 and SIM2 operated by operator 2. In determining the availability of the edge servers (106 a-106 n), enablement module 110 determines applications available at the edge servers (106 a-106 n) for SIM1 and SIM2. In examples herein, edge servers (106 a-106 n) available to SIM 1/operator 1 may include app a, app B, and app D. The edge servers (106 a to 106 n) available to SIM 1/operator 1 may include app C. Since the edge servers (106 a to 106 n) available to SIM 1/operator 1 include app a, the enablement module 110 selects SIM 1/operator 1 for the recommended application a. Thus, enablement module 110 suggests the user to watch the movie using app a and app a's SIM1.

Consider an example autonomous driving scenario as shown in fig. 15b, and UE 102 supports SIM1 for operator 1 and SIM2 for operator 2. The serving cell of cid 500 of the base station communicating with UE 102 may be operated by operator 1 and operator 2. Thus, enablement module 110 determines the availability of edge servers (106 a-106 n) for base stations (communicating with UE 102) with respect to operator 1 and operator 2. In the examples herein, edge servers (106 a-106 n) are available for SIM1 operated by operator 1 and SIM2 operated by operator 2.

In addition, enablement module 110 checks the characteristics of the network slices associated with SIM1 and SIM2. In examples herein, the characteristics of the network slice associated with SIM1 may include 1ms latency and services such as V2V, V2I, V2P, V2N, and so on. Characteristics of the network slice associated with SIM2 may include 5ms latency and services such as V2V, V2I, V2P, V2N. Since the latency of the network slice associated with SIM1 is 1ms, the enabling module 110 will provide a suggestion to the user to use SIM/operator 1 for an autopilot-related application.

Fig. 16a, 16b, 16c, and 16d are exemplary diagrams illustrating recommending a network slice from among one or more network slices associated with a SIM for a requested service according to embodiments disclosed herein.

Fig. 16a depicts an example diagram in which network slices may be recommended based on characteristics of one or more network slices associated with a SIM. Consider an example scenario as shown in fig. 16a, where network slice 1 and network slice 2 are network slices that are allowed for the same RAT/subscription. Network slice 1 and network slice 2 are eMBB (enhanced mobile broadband) network slices/service types (SSTs), but have different features. Further, network slice 1 has a throughput of 300Mbps and a latency of 1ms, and network slice 2 has a throughput of 500Mbps and a latency of 15ms. Thus, enablement module 110 may select network slice 1 for the SIM that may be used to complete the requested service. Additionally, the enablement module 110 can suggest to the user to purchase a network slice/subscription to complete the requested service.

Fig. 16b depicts an example diagram in which network slices may be recommended based on identification of an allowed set of network slices. Consider an example scenario in which the UE 102 has successfully completed its registration process. Upon successful completion of the registration process, the UE may obtain information about a set of allowed network slices for the registration area from the AMF instance that is serving the UE 102. When information about the set of allowed network slices is obtained, the enablement module 110 tracks the allowed network slices and recommends the network slice for the SIM to complete the requested service. The enablement module 110 may also provide an interface to the user for selecting a network slice for the requested service. Additionally, the enablement module 110 may suggest to the user to purchase a new network slice to complete the requested service.

Fig. 16c is an exemplary diagram illustrating extraction of network slice related information based on user selection of a network slice. Consider the example scenario shown in fig. 16c, where the user selects network slice 1 of SIM1 for recommending an application to complete the requested service. Based on the user selection, the enablement module 110 instructs the modem to send a Protocol Data Unit (PDU) session establishment request to the AMS to obtain details about the selected network slice. The detailed information may be, but is not limited to, a Data Network Name (DNN), an SSC pattern, and a session type.

Fig. 16d is an exemplary diagram illustrating a user mode for selecting a network slice for a particular service. Embodiments herein provide a user mode and an automatic mode for selecting a network slice. In the automatic mode, enablement module 110 selects a network slice of SIMs for a particular service based on the set user priorities (including cost benefit factors, performance factors, and best effort factors). In user mode, during application startup, the user may provide an option to select a SIM/network slice. Each option may contain details of the edge availability of a particular service. In addition, an interface may be provided to the user to select a notification form (badge notification/creation of folder) for indicating the availability of the edge server.

Fig. 17a and 17b are exemplary diagrams illustrating updating network capabilities based on a cell change to recommend at least one of a network slice and a RAT for a requested service according to embodiments disclosed herein.

As shown in fig. 17a, upon determining a cell location change, UE 102 checks for support of enabled layers for the changed cell location. Upon determining that the enabled layer does not support, the UE 102 checks the availability of previous information in the memory 108 for RTT and E2E delay. Upon determining the availability of the previous information for RTT and E2E delay, the UE 102 updates the local database with the RTT and E2E delay. Otherwise, the UE 102 calculates the RTT and E2E delay and updates the local database.

Upon determining support of the enablement layer, the UE 102 instructs the enablement module 110 to update the local database with the availability of the edge servers (106 a-106 n) of the one or more applications, as well as network slices, qoS, and other network parameters. Thus, the enablement module can use the updated local database (as shown in fig. 17 b) to recommend at least one of RAT/subscription and network slice to the user to complete the particular service.

Fig. 18 is an exemplary diagram illustrating feature-based quality of service (QoS) operations for call-related applications according to embodiments disclosed herein.

Embodiments herein enable the enablement module 110 to prioritize applications in determining unavailability of edge servers. To determine priority, the enabling module 110 assigns a 5QI value to the application and displays the 5QI value to the RAT to provide better bandwidth and latency. The higher 5QI value assigned to an application represents a RAT for providing better bandwidth and latency. In the examples herein, enablement module 110 may assign a 5QI for applications related to a call/OTT: 9 to obtain better bandwidth and latency for the applications associated with OTT.

Fig. 19 is an example flow diagram illustrating processing at least one of network slices and edge availability to recommend an application for a particular service in accordance with an embodiment disclosed herein. Consider an example scenario where an OTT call is placed by a user and further edge servers or network slices are not available to the OTT call application. In this case, enable module 110 checks whether at least one of the RTT and the E2E delay exceeds a limit. Upon determining that at least one of the RTT and the E2E delay exceeds the limit, the enablement module 110 suggests to the user to continue the call using the OTT app without the edge server (106 a-106 n)/network slice.

Upon determining that at least one of the RTT and the E2E delay does not exceed the limit, the enablement module 110 proposes to request an edge server (106 a-106 n) from the 5G core network, or to request a network slice from the AMF. The enablement module 110 can also suggest to the user to purchase the network slice. If the request is successfully registered, the enablement module 110 suggests the user to continue the OTT call using the edge server and the application for which the network slice is available.

FIG. 20 is an example diagram illustrating providing recommendations to complete a service (or services) at a particular location according to embodiments disclosed herein. For example, consider an example scenario as shown in fig. 20, where UE 102 communicates with a cell of cid 500 of a base station (104 a to 104 n). The edge servers (106 a to 106 n) may or may not be placed in the vicinity of the base station serving the cell of cid 500.

Upon receiving a request for a service (video streaming service, file download service, etc.) from a user at a particular location, enablement module 110 provides suggestions to the user to complete the service based on tracking available resources. Based on the request, the enablement module 110 provides an interface for the user to select factors for providing the suggestion. These factors may be, but are not limited to, edge servers, network slices, qoS, etc.

If the user selects an edge factor, the enablement module 110 provides suggestions to the user to complete the requested service based on the availability of edge servers. If the user selects a network slice for a particular service, the recommended application for the requesting service may be used based on the selected network slice. If the user selects a better QoS factor, the enabling module will prioritize applications that are unavailable to the edge server. The priority of the application may be determined by assigning a 5QI value. Furthermore, a 5QI value may be shared with the RAT/cell of cid 500 associated with the base station to provide better bandwidth and latency for the application. In the examples herein, enablement module 110 may convert 5QI:2 to live streaming and 5QI:4 are allocated to buffer streaming. Thus, the QoS of an application can be improved by prioritizing traffic for such application.

The embodiments disclosed herein may be implemented by at least one software program running on at least one hardware device and performing network management functions to control elements. The elements shown in fig. 1 and 2 may be at least one of a hardware device or a combination of a hardware device and a software module.

Embodiments disclosed herein describe methods and systems for providing recommendations for completing services on User Equipment (UE) at a particular location. It will therefore be appreciated that the scope of protection is extended to such programs and that such computer readable storage means, in addition to the computer readable means having messages therein, also contain: program code means for performing one or more steps of the method when the program is run on a server or a mobile device or any suitable programmable device. The method is implemented in embodiments by or together with a software program written in, for example, very high speed integrated circuit hardware description language (VHDL) or another programming language, or by one or more VHDLs or several software modules running on at least one hardware device. The hardware device may be any type of portable device that can be programmed. The apparatus may further comprise means which may be: such as a hardware device (e.g., ASIC), or a combination of hardware and software devices (e.g., ASIC and FPGA), or at least one microprocessor and at least one memory having software modules located therein. The method embodiments described herein may be implemented partly in hardware and partly in software. Alternatively, the present disclosure may be implemented on different hardware devices, for example, using multiple CPUs.

The foregoing description of the specific embodiments will so fully reveal the general nature of the embodiments herein that others can, by applying current knowledge, readily modify and/or adapt for various applications such specific embodiments without departing from the generic concept, and, therefore, such adaptations and modifications should and are intended to be comprehended within the meaning and range of equivalents of the disclosed embodiments. It is to be understood that the phraseology or terminology employed herein is for the purpose of description and not of limitation. Thus, while the embodiments herein have been described in terms of embodiments, those skilled in the art will recognize that the embodiments herein can be practiced with modification within the spirit and scope of the embodiments described herein.

While the present disclosure has been described with various embodiments, various changes and modifications may be suggested to one skilled in the art. The present disclosure is intended to embrace such alterations and modifications as fall within the scope of the appended claims.

Claims

1. A method for providing at least one recommendation for executing at least one service on a User Equipment (UE), the method comprising:

the UE obtaining a request from a user to perform at least one service;

the UE determining at least one network parameter corresponding to the requested at least one service;

the UE determines the at least one recommendation using the determined at least one network parameter, wherein the at least one recommendation includes a recommendation of at least one of: an application of at least one application supporting the at least one service, a RAT of at least one radio access technology, RAT, supported by the UE, a SIM of at least one SIM supported by the UE, a network slice of a network slice associated with the at least one SIM; and

the UE performs the requested at least one service using the determined at least one recommendation.

2. The method of claim 1, the method further comprising: the UE provides the determined at least one recommendation to the user to perform the at least one service.

3. The method of claim 1, wherein the at least one service comprises a multimedia streaming service, a call related service, a file download service, a carousel service, a Television (TV) service, and an on-demand media service.

4. The method of claim 1, wherein the at least one network parameter comprises at least one of Round Trip Time (RTT), end-to-end (E2E) delay, availability of at least one edge server, availability of network slices for at least one Subscriber Identity Module (SIM), characteristics of available network slices, billing details, signal conditions, and network load.

5. The method of claim 4, wherein determining the availability of the at least one edge server comprises:

upon determining a change in location of a cell associated with a base station in communication with the UE, the UE sending a registration request to a core network; and

the UE determines availability of the edge server and at least one application available on the edge server based on a registration response received from the core network in response to the registration request.

6. The method of claim 5, the method further comprising: the UE performs at least one User Interface (UI) -based action to indicate availability of the at least one edge server for the at least one application, wherein the at least one UI-based action comprises:

providing at least one badge notification to at least one application available on the at least one edge server; and

creating a folder based on the availability of the at least one edge server for the at least one application, wherein the folder includes the at least one application available at the at least one edge server.

7. The method of claim 5, further comprising: the UE uploads at least one content to the at least one available edge server, wherein the at least one content uploaded in the at least one available edge server is downloaded by at least one other UE.

8. The method of claim 4, wherein determining the availability of the at least one edge server comprises:

calculating an RTT for at least one application supporting the requested at least one service based on each of at least one cell associated with a base station communicating with the UE, wherein the requested at least one service is at least one throughput-based service;

averaging the RTTs calculated for at least one application supporting the requested at least one service; and

determining that the at least one edge server is available for the requested at least one service if the averaged RTT has a lowest value.

9. The method of claim 4, wherein determining the availability of the at least one edge server comprises:

calculating an E2E delay for at least one application supporting the at least one service based on each of at least one cell associated with a base station in communication with the UE, wherein the at least one service includes at least one call-based service;

averaging E2E delays calculated for at least one application supporting at least one service; and

determining that the at least one edge server is available for the requested at least one service if the averaged E2E has a lowest value.

10. The method of claim 1, wherein if the at least one recommendation comprises a recommendation of an application of at least one application supporting the at least one service, the method further comprises:

determining, by the UE, a network class of the at least one application based on the determined at least one network parameter; and is

Wherein the application is an application recommended from the at least one application using the determined network level.

11. The method of claim 10, wherein determining the at least one recommendation using the determined at least one network parameter comprises at least one of:

determining, by the UE, a recommendation of the RAT from the at least one RAT associated with the UE for the application determined for the at least one request, wherein the RAT is recommended with the determined network class for the at least one RAT associated with the UE;

determining, by the UE, a recommendation of the SIM for an application determined for at least one service from at least one SIM, wherein the SIM is determined using at least one of the network class determined for the at least one SIM and a characteristic of a network slice available to the at least one SIM; and

the UE determines a recommendation of the network slice of the SIM to be used for the application determined for the at least one service, wherein the network slice is determined using at least one of the network level determined for the at least one SIM and characteristics of the network slice available to the at least one SIM.

12. The method of claim 11, wherein user input is received to determine the SIM and the network slice of an application recommended for the at least one service.

13. A User Equipment (UE) supporting at least one Subscriber Identity Module (SIM) and at least one Radio Access Technology (RAT), the UE comprising:

a transceiver;

a memory; and

at least one processor coupled to the memory and the transceiver, wherein the at least one processor is configured to:

obtaining a request from a user to perform at least one service;

determining at least one network parameter corresponding to the requested at least one service;

determining at least one recommendation using the determined at least one network parameter, wherein the at least one recommendation comprises a recommendation of at least one of: an application of at least one application supporting the at least one service, a RAT of at least one radio access technology, RAT, supported by the UE, a SIM of at least one SIM supported by the UE, a network slice of a network slice associated with the at least one SIM; and

the requested at least one service is executed using the determined at least one recommendation.

14. The UE of claim 13, wherein the at least one processor is further configured to operate in accordance with one of the methods of claims 2 to 12.